Applications of Latent Dirichlet Allocation and Hierarchical Dirichlet Processes

Speaker:	Dr. Alice Oh
		Department of Computer Science
 		Korea Advanced Institute of Science and Technology

Title:		"Applications of Latent Dirichlet Allocation and
		 Hierarchical Dirichlet Processes"

Date:		Monday, 14 February 2011

Time:		4:00pm - 5:00pm

Venue:		Lecture Theatre F (near lifts 25/26), HKUST

Abstract:

Latent Dirichlet Allocation (LDA) and Hierarchical Dirichlet Processes
(HDP) have become popular models for discovering latent semantics from
text corpora. I will first start this talk with what LDA and HDP are and
how they are used in common text analysis tasks. Then, I will present
three recent papers from our research group that extend LDA and HDP to
analyze three different text corpora: online reviews, news articles, and
conference proceedings. With the online reviews, we propose a variant of
LDA called Aspect and Sentiment Unification Model (ASUM) to analyze topics
and sentiments jointly in an unsupervised fashion. With the news articles,
we use LDA to generate topic chains to model temporal patterns of similar
topics. With the conference proceedings, we propose a variant of HDP
called distant dependent Chinese Restaurant Franchise (ddCRF) to discover
how new topics emerge through time.

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Biography:

Alice Oh is an Assistant Professor of Computer Science at Korea Advanced
Institute of Science and Technology. She leads her research group, Users
and Information Lab, with the vision of delivering information to satisfy
the user. To that end, she studies and employs methods from machine
learning, human-computer interaction, and statistical natural language
processing. Alice completed her M.S. in Language and Information
Technologies at CMU and her Ph.D. in Computer Science at MIT.